haive.agents.reasoning_and_critique.self_discover.selector.agent¶
Self-Discover Selector Agent implementation.
Classes¶
Agent that selects relevant reasoning modules for a given task. |
Module Contents¶
- class haive.agents.reasoning_and_critique.self_discover.selector.agent.SelectorAgent(name='selector', engine=None, **kwargs)¶
Bases:
haive.agents.simple.SimpleAgentAgent that selects relevant reasoning modules for a given task.
The Selector Agent is the first stage in the Self-Discover workflow. It analyzes the task and selects 3-5 reasoning modules from the available options that would be most effective for solving the problem.
- name¶
Agent identifier (default: “selector”)
- engine¶
LLM configuration for the agent
Example
>>> from haive.core.engine.aug_llm import AugLLMConfig >>> >>> config = AugLLMConfig(temperature=0.3) >>> selector = SelectorAgent(engine=config) >>> >>> result = await selector.arun({ ... "available_modules": "1. Critical thinking\\n2. Pattern recognition...", ... "task_description": "Design a recommendation system" ... })
Initialize the Selector Agent.
- Parameters:
name (str) – Name for the agent
engine (haive.core.engine.aug_llm.AugLLMConfig) – LLM configuration (if not provided, creates default)
**kwargs – Additional arguments passed to SimpleAgent